from IPython.display import Image, display, HTML
Image('../img/title.jpg')
import sys
sys.path.insert(0, '../scripts/')
import pickle as pkl
import pandas as pd
import numpy as np
import seaborn as sns
from visualizer import scatter_3D, display_samples, get_fulllink
years = np.arange(2008, 2018)
df = pd.concat([pd.read_csv(f'../data/dataframes2/{y}.csv')
for y in years], axis=0).dropna()
with open("../data/transformed_data/scatter_dict_2008_2017.pkl","rb") as f:
scatter_dict = pkl.load(f)
X = scatter_dict['data']
labels = scatter_dict['labels']
colors = scatter_dict['colors']
with open("../data/transformed_data/cluster_dict.pkl","rb") as f:
cluster_dict = pkl.load(f)
df['cluster'] = cluster_dict['clusters']
agg_colors = cluster_dict['agg_colors']
scatter_3D(X[:, :3], agg_colors, labels)
themes = ['Labor Related', 'Properties and Taxes', 'Drug Cases', 'Rape',
'Murder/Kidnapping', 'Certiorari']
n_clusters = 6
palette = sns.color_palette('hls', n_colors=n_clusters).as_hex()
for i, thm in zip(np.arange(n_clusters), themes):
display(HTML(f'<h3 style="color:{palette[i]};">Cluster {i}: {thm}</h3>'))
for _, row in df[df.cluster==i].sample(n=3, random_state=42).iterrows():
display(HTML(f'<a href="{get_fulllink(row.link)}">{row.case_number}</a>'))
# print(get_fulllink(row.link))
Image('../img/how.jpg')
HTML('<img src="../img/lawphil.gif">')
# <img src="../img/lawphil.gif">
Image('../img/process.png')
scatter_3D(X[:, :3], colors, labels)
Image('../img/hierarchical.png', width=900)
display(HTML('<h2>Sample Case</h2>'))
Image('../img/sample_case.png', width=900)
Image('../img/top_recommendation1.png', width=900)
Image('../img/top_recommendation2.png', width=900)
Image('../img/top_recommendation3.png', width=900)